How deep learning is accelerating multiscale design of porous electrodes for flow cells
Peer-Reviewed Publication
Updates every hour. Last Updated: 20-Dec-2025 04:11 ET (20-Dec-2025 09:11 GMT/UTC)
Researchers from The Hong Kong University of Science and Technology and the Southern University of Science and Technology have developed a novel deep learning neural network, Electrode Net. By introducing signed distance fields and three-dimensional convolutional neural networks, this method can significantly accelerate electrode design while maintaining high accuracy. It is widely applicable to fuel cells, water electrolyzers, flow batteries, etc.
Additive manufacturing, also known as 3D printing, has proven transformative for fabricating electrically conductive polymer nanocomposites that incorporate carbon nanotubes. However, existing methods struggle to achieve high stretchability while maintaining electrical conductivity, limiting practical applicability. Now, researchers from Korea have developed highly stretchable carbon nanotube-nanocomposites, optimized specifically for vat photopolymerization type 3D printing. Using these materials, they also developed a wearable smart-insole sensing platform for real-time foot pressure monitoring.
A novel strategy was designed for guiding supramolecular macrocycles into nanoscale chiral topological toroids, establishing hierarchical self-assembly pathways for advanced chiroptical materials
A novel strategy was designed for guiding supramolecular macrocycles into nanoscale chiral topological toroids, establishing hierarchical self-assembly pathways for advanced chiroptical materials
Cultured neural tissues have been widely used as a simplified experimental model for brain research. However, existing devices for growing and recording neural tissues, which are manufactured using semiconductor processes, have limitations in terms of shape modification and the implementation of three-dimensional (3D) structures.
By "thinking outside the box," a KAIST research team has successfully created a customized 3D neural chip. They first used a 3D printer to fabricate a hollow channel structure, then used capillary action to automatically fill the channels with conductive ink, creating the electrodes and wiring. This achievement is expected to significantly increase the design freedom and versatility of brain science and brain engineering research platforms.
In 2024, 3.4 billion people lacked safely managed sanitation
Sustainable Development Goal 6 has a target to achieve access to adequate and equitable sanitation and hygiene for all by 2030
Portable toilet service of container-based sanitation is having a positive impact
An international study on container-based sanitation (CBS) systems has found that this portable toilet option significantly improves the quality of life for people living in urban slums in Kenya, Peru and South Africa.
CBS systems use sealed, portable toilet containers that are collected, emptied, and cleaned regularly as part of a subscription-based service. Unlike traditional sanitation solutions that require heavy infrastructure, CBS offers a flexible and practical alternative for densely populated urban areas.
In August, Pensoft had the honour of welcoming colleagues from the Vietnam Academy of Science and Technology (VAST) to the headquarters of the open-access scholarly publisher and technology provider in Sofia, Bulgaria. The visit was marked by engaging discussions on scholarly publishing, future innovations, current challenges in academia and potential collaborations. The highlight of the meeting was the formal signing of a Memorandum of Understanding (MoU) between Prof. Dr. Lyubomir Penev, Pensoft’s CEO and founder, and Prof. Dr. Thai Hoang, Vice Chairman of the Scientific Council of Materials Science at VAST and the Editor‑in‑Chief of the Vietnam Journal of Science and Technology.